Application of Neural Networks for Event-by-Event Evaluation of the Impact Parameter

被引：0
|
作者：
Galaktionov, K. [1 ]
Rudnev, V. [1 ]
Valiev, F. [1 ]
机构：
[1] St Petersburg State Univ, St Petersburg 198504, Russia
来源：
PHYSICS OF PARTICLES AND NUCLEI | 2023年 / 54卷 / 03期
基金：
俄罗斯基础研究基金会;
关键词：
D O I：
10.1134/S1063779623030152
中图分类号：
O412 [相对论、场论]; O572.2 [粒子物理学];
学科分类号：
摘要：
Evaluation of the impact parameter in single events is crucial for the correct and efficient data processing in collision-based nuclear and particle physics experiments. Estimating the impact parameter in real time allows experimentalists to preselect the most informative events at the data acquisition stage before any processing. The presented computational experiments show the applicability of neural networks combined with the microchannel plate detectors to directly estimate the impact parameter at the experimental facilities under construction.
引用
收藏
页码：446 / 448
页数：3
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